, including all inherited members.
_classname_() | PLearn::ConditionalDensityNet | [static] |
_getOptionList_() | PLearn::ConditionalDensityNet | [static] |
_getRemoteMethodMap_() | PLearn::ConditionalDensityNet | [static] |
_isa_(const Object *o) | PLearn::ConditionalDensityNet | [static] |
_new_instance_for_typemap_() | PLearn::ConditionalDensityNet | [static] |
_static_initialize_() | PLearn::ConditionalDensityNet | [static] |
_static_initializer_ | PLearn::ConditionalDensityNet | [static] |
a | PLearn::ConditionalDensityNet | [protected] |
asString() const | PLearn::Object | [virtual] |
asStringRemoteTransmit() const | PLearn::Object | [virtual] |
b | PLearn::ConditionalDensityNet | [protected] |
b_costs | PLearn::PLearner | [mutable, protected] |
b_inputs | PLearn::PLearner | [mutable, protected] |
b_outputs | PLearn::PLearner | [mutable, protected] |
b_targets | PLearn::PLearner | [mutable, protected] |
b_weights | PLearn::PLearner | [mutable, protected] |
batch_size | PLearn::ConditionalDensityNet | |
batchComputeOutputAndConfidence(VMat inputs, real probability, VMat outputs_and_confidence) const | PLearn::PLearner | [virtual] |
bias_decay | PLearn::ConditionalDensityNet | |
build() | PLearn::ConditionalDensityNet | [virtual] |
build_() | PLearn::ConditionalDensityNet | [private] |
build_from_train_set() | PLearn::PLearner | [inline, protected, virtual] |
c | PLearn::ConditionalDensityNet | [protected] |
c_penalization | PLearn::ConditionalDensityNet | |
call(const string &methodname, int nargs, PStream &io) | PLearn::Object | [virtual] |
cdf(const Vec &x) const | PLearn::ConditionalDensityNet | [virtual] |
cdf_f | PLearn::ConditionalDensityNet | [mutable] |
centers | PLearn::ConditionalDensityNet | [protected] |
centers_initialization | PLearn::ConditionalDensityNet | |
centers_M | PLearn::ConditionalDensityNet | [protected] |
changeOption(const string &optionname, const string &value) | PLearn::Object | |
changeOptions(const map< string, string > &name_value) | PLearn::Object | [virtual] |
classname() const | PLearn::ConditionalDensityNet | [virtual] |
computeConfidenceFromOutput(const Vec &input, const Vec &output, real probability, TVec< pair< real, real > > &intervals) const | PLearn::PLearner | [virtual] |
computeCostsFromOutputs(const Vec &input, const Vec &output, const Vec &target, Vec &costs) const | PLearn::PDistribution | [virtual] |
computeCostsOnly(const Vec &input, const Vec &target, Vec &costs) const | PLearn::PLearner | [virtual] |
computeInputOutputConfMat(VMat inputs, real probability) const | PLearn::PLearner | |
computeInputOutputMat(VMat inputs) const | PLearn::PLearner | |
computeOutput(const Vec &input, Vec &output) const | PLearn::PDistribution | [virtual] |
computeOutputAndCosts(const Vec &input, const Vec &target, Vec &output, Vec &costs) const | PLearn::PLearner | [virtual] |
computeOutputConfMat(VMat inputs, real probability) const | PLearn::PLearner | |
computeOutputCovMat(const Mat &inputs, Mat &outputs, TVec< Mat > &covariance_matrices) const | PLearn::PLearner | [virtual] |
computeOutputs(const Mat &input, Mat &output) const | PLearn::PLearner | [virtual] |
computeOutputsAndCosts(const Mat &input, const Mat &target, Mat &output, Mat &costs) const | PLearn::PLearner | [virtual] |
ConditionalDensityNet() | PLearn::ConditionalDensityNet | |
costs | PLearn::ConditionalDensityNet | [protected] |
cum_denominator | PLearn::ConditionalDensityNet | [protected] |
cum_numerator | PLearn::ConditionalDensityNet | [protected] |
cumulative | PLearn::ConditionalDensityNet | [protected] |
curve_positions | PLearn::ConditionalDensityNet | |
declareMethods(RemoteMethodMap &rmm) | PLearn::PDistribution | [protected, static] |
declareOptions(OptionList &ol) | PLearn::ConditionalDensityNet | [protected, static] |
declaringFile() | PLearn::ConditionalDensityNet | [inline, static] |
deepCopy(CopiesMap &copies) const | PLearn::ConditionalDensityNet | [virtual] |
deepCopyNoMap() | PLearn::Object | |
delta_curve | PLearn::PDistribution | [protected] |
delta_steps | PLearn::ConditionalDensityNet | [protected] |
density | PLearn::ConditionalDensityNet | [protected] |
PLearn::PDistribution::density(const Vec &y) const | PLearn::PDistribution | [virtual] |
density_f | PLearn::ConditionalDensityNet | [mutable] |
direct_in_to_out | PLearn::ConditionalDensityNet | |
direct_in_to_out_weight_decay | PLearn::ConditionalDensityNet | |
expdir | PLearn::PLearner | |
expectation(Vec &mu) const | PLearn::ConditionalDensityNet | [virtual] |
expected_value | PLearn::ConditionalDensityNet | [protected] |
f | PLearn::ConditionalDensityNet | [mutable] |
finalize() | PLearn::PLearner | [virtual] |
finalized | PLearn::PLearner | |
forget() | PLearn::ConditionalDensityNet | [virtual] |
forget_when_training_set_changes | PLearn::PLearner | [protected] |
generate(Vec &x) const | PLearn::ConditionalDensityNet | [virtual] |
generate_precision | PLearn::ConditionalDensityNet | |
generateJoint(Vec &xy) | PLearn::PDistribution | [virtual] |
generateJoint(Vec &x, Vec &y) | PLearn::PDistribution | |
generateN(const Mat &Y) const | PLearn::PDistribution | [virtual] |
generatePredicted(Vec &y) | PLearn::PDistribution | [virtual] |
generatePredictor(Vec &x) | PLearn::PDistribution | [virtual] |
generatePredictorGivenPredicted(Vec &x, const Vec &y) | PLearn::PDistribution | [virtual] |
getExperimentDirectory() const | PLearn::PLearner | [inline] |
getNPredicted() const | PLearn::PDistribution | [inline] |
getNPredictor() const | PLearn::PDistribution | [inline] |
getOption(const string &optionname) const | PLearn::Object | |
getOptionList() const | PLearn::ConditionalDensityNet | [virtual] |
getOptionMap() const | PLearn::ConditionalDensityNet | [virtual] |
getOptionsToRemoteTransmit() const | PLearn::Object | [virtual] |
getOptionsToSave() const | PLearn::Object | [virtual] |
getOutputNames() const | PLearn::PLearner | [virtual] |
getRemoteMethodMap() const | PLearn::ConditionalDensityNet | [virtual] |
getTestCostIndex(const string &costname) const | PLearn::PLearner | |
getTestCostNames() const | PLearn::PDistribution | [virtual] |
getTrainCostIndex(const string &costname) const | PLearn::PLearner | |
getTrainCostNames() const | PLearn::ConditionalDensityNet | [virtual] |
getTrainingSet() const | PLearn::PLearner | [inline] |
getTrainStatsCollector() | PLearn::PLearner | [inline] |
getValidationSet() const | PLearn::PLearner | [inline] |
hasOption(const string &optionname) const | PLearn::Object | |
in2distr_f | PLearn::ConditionalDensityNet | [mutable] |
info() const | PLearn::Object | [virtual] |
inherited typedef | PLearn::ConditionalDensityNet | [private] |
initial_hardness | PLearn::ConditionalDensityNet | |
initial_hardnesses | PLearn::ConditionalDensityNet | [protected] |
initialize_mu(Vec &mu_) | PLearn::ConditionalDensityNet | |
initializeParams() | PLearn::ConditionalDensityNet | |
initTrain() | PLearn::PLearner | [protected] |
input | PLearn::ConditionalDensityNet | [protected] |
inputsize() const | PLearn::PLearner | [virtual] |
inputsize_ | PLearn::PLearner | [protected] |
invars | PLearn::ConditionalDensityNet | [protected] |
isStatefulLearner() const | PLearn::PLearner | [virtual] |
L1_penalty | PLearn::ConditionalDensityNet | |
layer1_bias_decay | PLearn::ConditionalDensityNet | |
layer1_weight_decay | PLearn::ConditionalDensityNet | |
layer2_bias_decay | PLearn::ConditionalDensityNet | |
layer2_weight_decay | PLearn::ConditionalDensityNet | |
load(const PPath &filename) | PLearn::Object | [virtual] |
log_density(const Vec &x) const | PLearn::ConditionalDensityNet | [virtual] |
log_likelihood_vs_squared_error_balance | PLearn::ConditionalDensityNet | |
lower_bound | PLearn::PDistribution | |
makeDeepCopyFromShallowCopy(CopiesMap &copies) | PLearn::ConditionalDensityNet | [virtual] |
mass_cost | PLearn::ConditionalDensityNet | |
master_sends_testset_rows | PLearn::PLearner | |
maxY | PLearn::ConditionalDensityNet | |
mean_f | PLearn::ConditionalDensityNet | [mutable] |
minus_prev_centers_0 | PLearn::ConditionalDensityNet | [protected] |
minus_scaled_prev_centers_0 | PLearn::ConditionalDensityNet | [protected] |
missingExpectation(const Vec &input, Vec &mu) | PLearn::PDistribution | [virtual] |
mu | PLearn::ConditionalDensityNet | |
mu_is_fixed | PLearn::ConditionalDensityNet | |
n_curve_points | PLearn::PDistribution | |
n_examples | PLearn::PLearner | [protected] |
n_output_density_terms | PLearn::ConditionalDensityNet | |
n_predicted | PLearn::PDistribution | [mutable, protected] |
n_predictor | PLearn::PDistribution | [mutable, protected] |
newread(PStream &in, unsigned int id=UINT_MAX) | PLearn::Object | |
newwrite(PStream &out) const | PLearn::Object | [virtual] |
nhidden | PLearn::ConditionalDensityNet | |
nhidden2 | PLearn::ConditionalDensityNet | |
nservers | PLearn::PLearner | |
nstages | PLearn::PLearner | |
nTestCosts() const | PLearn::PLearner | [virtual] |
nTrainCosts() const | PLearn::PLearner | [virtual] |
Object(bool call_build_=false) | PLearn::Object | |
oldread(istream &in) | PLearn::Object | [virtual] |
optimizer | PLearn::ConditionalDensityNet | |
output | PLearn::ConditionalDensityNet | [protected] |
output_and_target | PLearn::ConditionalDensityNet | |
output_and_target_to_cost | PLearn::ConditionalDensityNet | [mutable] |
output_and_target_values | PLearn::ConditionalDensityNet | |
output_layer_bias_decay | PLearn::ConditionalDensityNet | |
output_layer_weight_decay | PLearn::ConditionalDensityNet | |
outputs | PLearn::ConditionalDensityNet | [protected] |
outputs_def | PLearn::PDistribution | |
outputsize() const | PLearn::PDistribution | [virtual] |
parallelize_here | PLearn::PLearner | |
params | PLearn::ConditionalDensityNet | [protected] |
paramsvalues | PLearn::ConditionalDensityNet | |
parseOptionName(const string &optionname, Object *&final_object, OptionList::iterator &option_iter, string &option_index) | PLearn::Object | |
parseOptionName(const string &optionname, const Object *&final_object, OptionList::iterator &option_iter, string &option_index) const | PLearn::Object | |
PDistribution() | PLearn::PDistribution | |
penalties | PLearn::ConditionalDensityNet | [protected] |
penalty_type | PLearn::ConditionalDensityNet | |
PLearner() | PLearn::PLearner | |
pos_a | PLearn::ConditionalDensityNet | [protected] |
pos_b | PLearn::ConditionalDensityNet | [protected] |
pos_c | PLearn::ConditionalDensityNet | [protected] |
pos_y_cost | PLearn::ConditionalDensityNet | |
PPointable() | PLearn::PPointable | [inline] |
PPointable(const PPointable &other) | PLearn::PPointable | [inline] |
predicted_part | PLearn::PDistribution | [mutable, protected] |
predicted_size | PLearn::PDistribution | [protected] |
predictor_part | PLearn::PDistribution | [mutable, protected] |
predictor_size | PLearn::PDistribution | [protected] |
prepareToSendResults(PStream &out, int nres) | PLearn::Object | [static] |
prev_centers | PLearn::ConditionalDensityNet | [protected] |
prev_centers_M | PLearn::ConditionalDensityNet | [protected] |
processDataSet(VMat dataset) const | PLearn::PLearner | [virtual] |
random_gen | PLearn::PLearner | [mutable, protected] |
read(istream &in) | PLearn::Object | [virtual] |
readOptionVal(PStream &in, const string &optionname, unsigned int id=UINT_MAX) | PLearn::Object | |
ref() const | PLearn::PPointable | [inline] |
remote_generate() | PLearn::PDistribution | |
remote_test(VMat testset, PP< VecStatsCollector > test_stats, bool rtestoutputs, bool rtestcosts) const | PLearn::PLearner | [virtual] |
remote_useOnTrain() const | PLearn::PLearner | [virtual] |
report_progress | PLearn::PLearner | |
resetGenerator(long g_seed) | PLearn::ConditionalDensityNet | [virtual] |
resetInternalState() | PLearn::PLearner | [virtual] |
run() | PLearn::Object | [virtual] |
sampleweight | PLearn::ConditionalDensityNet | [protected] |
save(const PPath &filename) const | PLearn::Object | [virtual] |
save_trainingset_prefix | PLearn::PLearner | |
scale | PLearn::ConditionalDensityNet | |
scaled_prev_centers | PLearn::ConditionalDensityNet | [protected] |
scaled_prev_centers_M | PLearn::ConditionalDensityNet | [protected] |
seed_ | PLearn::PLearner | |
separate_mass_point | PLearn::ConditionalDensityNet | |
setExperimentDirectory(const PPath &the_expdir) | PLearn::PLearner | [virtual] |
setInput(const Vec &input) const | PLearn::ConditionalDensityNet | [virtual] |
setOption(const string &optionname, const string &value) | PLearn::Object | |
setPredictor(const Vec &predictor, bool call_parent=true) const | PLearn::PDistribution | [virtual] |
setPredictorPredictedSizes(int the_predictor_size, int the_predicted_size, bool call_parent=true) | PLearn::PDistribution | [virtual] |
setTrainingSet(VMat training_set, bool call_forget=true) | PLearn::PLearner | [virtual] |
setTrainStatsCollector(PP< VecStatsCollector > statscol) | PLearn::PLearner | [virtual] |
setValidationSet(VMat validset) | PLearn::PLearner | [virtual] |
splitCond(const Vec &input) const | PLearn::PDistribution | [protected] |
stage | PLearn::PLearner | |
steps | PLearn::ConditionalDensityNet | [protected] |
steps_0 | PLearn::ConditionalDensityNet | [protected] |
steps_gradient | PLearn::ConditionalDensityNet | [protected] |
steps_integral | PLearn::ConditionalDensityNet | [protected] |
steps_M | PLearn::ConditionalDensityNet | [protected] |
steps_type | PLearn::ConditionalDensityNet | |
store_cov | PLearn::PDistribution | [mutable, protected] |
store_expect | PLearn::PDistribution | [mutable, protected] |
store_result | PLearn::PDistribution | [mutable, protected] |
sub_test(VMat testset, PP< VecStatsCollector > test_stats, bool rtestoutputs, bool rtestcosts) const | PLearn::PLearner | [virtual] |
survival_fn(const Vec &x) const | PLearn::ConditionalDensityNet | [virtual] |
target | PLearn::ConditionalDensityNet | [protected] |
targetsize() const | PLearn::PLearner | [virtual] |
targetsize_ | PLearn::PLearner | [protected] |
test(VMat testset, PP< VecStatsCollector > test_stats, VMat testoutputs=0, VMat testcosts=0) const | PLearn::PLearner | [virtual] |
test_costf | PLearn::ConditionalDensityNet | [mutable] |
test_costs | PLearn::ConditionalDensityNet | [protected] |
test_minibatch_size | PLearn::PLearner | |
thresholdY | PLearn::ConditionalDensityNet | |
totalcost | PLearn::ConditionalDensityNet | |
train() | PLearn::ConditionalDensityNet | [virtual] |
train_set | PLearn::PLearner | [protected] |
train_stats | PLearn::PLearner | [protected] |
training_cost | PLearn::ConditionalDensityNet | [protected] |
unconditional_cdf | PLearn::ConditionalDensityNet | [protected] |
unconditional_delta_cdf | PLearn::ConditionalDensityNet | [protected] |
unconditional_p0 | PLearn::ConditionalDensityNet | |
unknownOutput(char def, const Vec &input, Vec &output, int &k) const | PLearn::PDistribution | [protected, virtual] |
unref() const | PLearn::PPointable | [inline] |
upper_bound | PLearn::PDistribution | |
usage() const | PLearn::PPointable | [inline] |
use(VMat testset, VMat outputs) const | PLearn::PLearner | [virtual] |
use_a_separate_random_generator_for_testing | PLearn::PLearner | |
useOnTrain(Mat &outputs) const | PLearn::PLearner | [virtual] |
validation_set | PLearn::PLearner | [protected] |
variance(Mat &cov) const | PLearn::ConditionalDensityNet | [virtual] |
verbosity | PLearn::PLearner | |
w1 | PLearn::ConditionalDensityNet | [protected] |
w2 | PLearn::ConditionalDensityNet | [protected] |
wdirect | PLearn::ConditionalDensityNet | [protected] |
weight_decay | PLearn::ConditionalDensityNet | |
weightsize() const | PLearn::PLearner | [virtual] |
weightsize_ | PLearn::PLearner | [protected] |
wout | PLearn::ConditionalDensityNet | [protected] |
write(ostream &out) const | PLearn::Object | [virtual] |
writeOptionVal(PStream &out, const string &optionname) const | PLearn::Object | |
y_values | PLearn::ConditionalDensityNet | |
~Object() | PLearn::Object | [virtual] |
~PPointable() | PLearn::PPointable | [inline, virtual] |